Within the last decade, there are growing economic/social incentives and opportunities for secondary use of data in many sectors, and strong market forces currently drive the active development of systems that aggregate user data gathered by many sources. This secondary use of data poses privacy threats due to unwanted use of data for the wrong purposes such as discriminating the user for employment, loan and insurance. Traditional privacy policy languages such as the Platform for Privacy Preferences (P3P) are inadequate since they were designed long before many of these technologies were invented and basically focus on enabling user-awareness and control during primary data collection (e.g. by a website). However, with the advent of Web 2.0 and Social Networking Sites, the landscape of privacy is shifting from limiting collection of data by websites to ensuring ethical use of the data after initial collection. To meet the current challenges of privacy protection in secondary context, we propose a privacy policy language, Purpose-to-Use (P2U), aimed at enforcing privacy while enabling secondary user information sharing across applications, devices, and services on the Web.

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Mobile and smart devices can play important roles in service provisioning and consumption in a grid-based service infrastructure. However, these devices and their unstable network are plagued with challenging issues that have made their integration with grid infrastructure a serious burden. Intermittent connectivity, bandwidth fluctuation, low memory, among others, cause high responsiveness in service delivery when these devices are used for service access. Adaptation capabilities can be very useful at addressing these issues. Therefore, this paper presents a utility function based Context Aware Adaptation Model(CAAM) that can monitor the service client's context, and uses a utility function based algorithm to take self reconfiguration decision in order to adapt the interaction between service consumers and service providers. Results from simulation experiments carried out on the model proved that adaptation is very useful at addressing problem of high responsiveness thereby improving on the quality of service.

The increasing availability of enormous data about users online, along with availability of sophisticated tools and technology to store, aggregate, and analyze data for secondary use has raised concerns about how to balance the opportunity for secondary use of data with the need to protect the user privacy that may result from harmful use. To develop a privacy protection mechanism that is useful and meets the expectations and needs of the user, it is important to understand user's attitude to privacy and secondary information sharing and usage of his/her data. While several studies have investigated factors influencing user's attitude to privacy in primary data collection context, none of the existing studies have provided an understanding of user perception and attitude to privacy in secondary context. To fill this gap, this work has identified five factors that are important in a secondary usage context and carried out a study on their influence on user's perception with respect to how their data is shared for secondary use. The main contribution of this paper is an understanding of factors influencing user decisions about privacy in secondary context, which can assist both technology designers and policy makers in the development of appropriate privacy protection that meets the needs and expectations of the user.

In many research and business domains, there are efforts to develop systems that aggregate user data gathered by various data sources. This approach involves secondary sharing of user data and potentially benefits the user in terms of improved personalization and better experience. However, concerns regarding privacy arise when sharing user data with unknown third parties. These concerns can be alleviated at two stages: i) ensuring selective control of the applications to share user data with, and ii) monitoring and penalizing errant data consumers who violate the terms of their contractual agreement and potentially abuse user data. This paper addresses the second stage of data use contract enforcement.We propose a trust management mechanism for monitoring data consumers' compliance to the contractual agreements for which data was shared with them. The trust mechanism is based on user complaints about suspected privacy violations and is able to identify the data consumers who are responsible. The framework penalizes the data consumer found guilty of violating its data use agreement by decreasing its trust value. This makes the data consumer less likely to be selected to receive user data, and limits its participation in the user data marketplace, forcing it to pay a higher price for purchase of user data.